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Jia Y, Li Y, Bai X, Liu L, Shan Y, Wang F, Yu Z, Zheng C. Raman Spectroscopy and Exosome-Based Machine Learning Predicts the Efficacy of Neoadjuvant Therapy for HER2-Positive Breast Cancer. Anal Chem 2025; 97:1374-1385. [PMID: 39780544 DOI: 10.1021/acs.analchem.4c05833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
Early prediction of the neoadjuvant therapy efficacy for HER2-positive breast cancer is crucial for personalizing treatment and enhancing patient outcomes. Exosomes, which play a role in tumor development and treatment response, are emerging as potential biomarkers for cancer diagnosis and efficacy prediction. Despite their promise, current exosome detection and isolation methods are cumbersome and time-consuming and often yield limited purity and quantity. In this study, we employed Raman spectroscopy to analyze the molecular changes in exosomes from the sera of HER2-positive breast cancer patients before and after two cycles of neoadjuvant therapy. Utilizing machine learning techniques (PCA, LDA, and SVM), we developed a predictive model with an AUC value exceeding 0.89. Additionally, we introduced an innovative HER2-positive exosome capture and detection system, termed Magnetic beads@HER2-Exos@HER2-SERS detection nanoprobes (HER2-MEDN). This system enabled us to efficiently extract and analyze HER2-positive exosomes, refining our predictive model to achieve an accuracy greater than 0.94. Our study has demonstrated the potential of the HER2-MEDN system in accurately predicting early treatment response, offering novel insights and methodologies for assessing the efficacy of neoadjuvant therapy in HER2-positive breast cancer.
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Affiliation(s)
- Yining Jia
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
| | - Yongqi Li
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
| | - Xintong Bai
- School of Mathematics, Shandong University, Jinan, Shandong 250100, China
| | - Liyuan Liu
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
| | - Ying Shan
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
| | - Fei Wang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
| | - Zhigang Yu
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
| | - Chao Zheng
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, Shandong 250033, China
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Kim EY, Lee KH, Yun JS, Park YL, Park CH, Jang SY, Ryu JM, Lee SK, Chae BJ, Lee JE, Kim SW, Nam SJ, Yu JH. Impact of residual microcalcifcations on prognosis after neoadjuvant chemotherapy in breast cancer patients. BMC Womens Health 2024; 24:187. [PMID: 38509531 PMCID: PMC10956337 DOI: 10.1186/s12905-024-02973-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 02/14/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND Residual microcalcifications after neoadjuvant chemotherapy (NAC) are challenging for deciding extent of surgery and questionable for impact on prognosis. We investigated changes in the extent and patterns of microcalcifications before and after NAC and correlated them with pathologic response. We also compared prognosis of patients depending on presence of residual microcalcifications after NAC. METHODS A total of 323 patients with invasive breast carcinoma treated with neoadjuvant chemotherapy at Kangbuk Samsung Hospital and Samsung Medical center from March 2015 to September 2018 were included. Patients were divided into four groups according to pathologic response and residual microcalcifications. Non-pCRw/mic group was defined as breast non-pCR with residual microcalcifications. Non-pCRw/o mic group was breast non-pCR without residual microcalcifications. pCRw/mic group was breast pCR with residual microcalcifications. pCRw/o mic group was breast pCR without residual microcalcifications. The first aim of this study is to investigate changes in the extent and patterns of microcalcifications before and after NAC and to correlate them with pathologic response. The second aim is to evaluate oncologic outcomes of residual microcalcifications according to pathologic response after NAC. RESULTS There were no statistical differences in the extent, morphology, and distribution of microcalcifications according to pathologic response and subtype after NAC (all p > 0.05). With a median follow-up time of 71 months, compared to pCRw/o mic group, the hazard ratios (95% confidence intervals) for regional recurrence were 5.190 (1.160-23.190) in non-pCRw/mic group and 5.970 (1.840-19.380) in non-pCRw/o mic group. Compared to pCRw/o mic group, the hazard ratios (95% CI) for distant metastasis were 8.520 (2.130-34.090) in non-pCRw/mic group, 9.120 (2.850-29.200) in non-pCRw/o mic group. Compared to pCRw/o mic, the hazard ratio (95% CI) for distant metastasis in pCRw/mic group was 2.240 (0.230-21.500) without statistical significance (p = 0.486). CONCLUSIONS Regardless of residual microcalcifications, patients who achieved pCR showed favorable long term outcome compared to non-pCR group.
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Affiliation(s)
- Eun Young Kim
- Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kwan Ho Lee
- Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Ji-Sup Yun
- Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Yong Lai Park
- Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Chan Heun Park
- Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sung Yoon Jang
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Jai Min Ryu
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Se Kyung Lee
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Byung-Joo Chae
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Jeong Eon Lee
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Seok Won Kim
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Seok Jin Nam
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea
| | - Jong Han Yu
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul, 06351, Republic of Korea.
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Kjeldsted E, Ammitzbøll G, Jørgensen LB, Lodin A, Bojesen RD, Ceballos SG, Rosthøj S, Lænkholm AV, Skou ST, Jack S, Gehl J, Dalton SO. Neo-train: study protocol and feasibility results for a two-arm randomized controlled trial investigating the effect of supervised exercise during neoadjuvant chemotherapy on tumour response in patients with breast cancer. BMC Cancer 2023; 23:777. [PMID: 37598196 PMCID: PMC10439618 DOI: 10.1186/s12885-023-11284-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 08/09/2023] [Indexed: 08/21/2023] Open
Abstract
BACKGROUND Prehabilitation with exercise interventions during neoadjuvant chemotherapy (NACT) is effective in reducing physical and psychosocial chemotherapy-related adverse events in patients with cancer. In preclinical studies, data also support a growth inhibitory effect of aerobic exercise on the tumour microenvironment with possible improved chemotherapy delivery but evidence in human patients is limited. The aim of the study here described is to investigate if supervised exercise with high-intensity aerobic and resistance training during NACT can improve tumour reduction in patients with breast cancer. METHODS This parallel two-armed randomized controlled trial is planned to include 120 women aged ≥ 18 years with newly diagnosed breast cancer starting standard NACT at a university hospital in Denmark (a total of 90 participants needed according to the power calculation and allowing 25% (n = 30) dropout). The participants will be randomized to usual care or supervised exercise consisting of high-intensity interval training on a stationary exercise bike and machine-based progressive resistance training offered three times a week for 24 weeks during NACT, and screening-based advice to seek counselling in case of moderate-severe psychological distress (Neo-Train program). The primary outcome is tumour size change (maximum diameter of the largest lesion in millimetre) measured by magnetic resonance imaging prior to surgery. Secondary outcomes include clinical/pathological, physical and patient-reported measures such as relative dose intensity of NACT, hospital admissions, body composition, physical fitness, muscle strength, health-related quality of life, general anxiety, depression, and biological measures such as intratumoural vascularity, tumour infiltrating lymphocytes, circulating tumour DNA and blood chemistry. Outcomes will be measured at baseline (one week before to 1-2 weeks after starting NACT), during NACT (approximately week 7, 13 and 19), pre-surgery (approximately week 21-29), at surgery (approximately week 21-30) and 3 months post-surgery (approximately 33-42 weeks from baseline). DISCUSSION This study will provide novel and important data on the potential benefits of supervised aerobic and resistance exercise concomitant to NACT on tumour response and the tumour microenvironment in patients with breast cancer, with potential importance for survival and risk of recurrence. If effective, our study may help increase focus of exercise as an active part of the neoadjuvant treatment strategy. TRIAL REGISTRATION The trial was registered at ClinicalTrials.gov (NCT04623554) on November 10, 2020.
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Affiliation(s)
- Eva Kjeldsted
- Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Rådmannsengen 5, Naestved, 4700, Denmark.
- Survivorship and Inequality in Cancer, Danish Cancer Institute, Strandboulevarden 49, Copenhagen, 2100, Denmark.
- Danish Research Centre for Equality in Cancer (COMPAS), Rådmannsengen 5, Naestved, 4700, Denmark.
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, Copenhagen, 2200, Denmark.
| | - Gunn Ammitzbøll
- Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Rådmannsengen 5, Naestved, 4700, Denmark
- Survivorship and Inequality in Cancer, Danish Cancer Institute, Strandboulevarden 49, Copenhagen, 2100, Denmark
- Danish Research Centre for Equality in Cancer (COMPAS), Rådmannsengen 5, Naestved, 4700, Denmark
| | - Lars Bo Jørgensen
- Department of Physiotherapy and Occupational Therapy, Zealand University Hospital, Sygehusvej 10, Roskilde, 4000, Denmark
- Department of Physiotherapy and Occupational Therapy, The Research Unit PROgrez, Naestved- Slagelse-Ringsted Hospitals, Faelledvej 2C, 1, Slagelse, 4200, Denmark
- Department of Sports Science and Clinical Biomechanics, Research Unit for Musculoskeletal Function and Physiotherapy, University of Southern Denmark, Campusvej 55, Odense, 5230, Denmark
| | - Alexey Lodin
- Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Rådmannsengen 5, Naestved, 4700, Denmark
| | - Rasmus Dahlin Bojesen
- Department of Surgery, Naestved-Slagelse-Ringsted Hospitals, Faelledvej 11, Slagelse, 4200, Denmark
- Center for Surgical Science, Department of Surgery, Zealand University Hospital, Lykkebaekvej 1, Køge, 4600, Denmark
| | | | - Susanne Rosthøj
- Statistics & Data Analysis, Danish Cancer Institute, Strandboulevarden 49, Copenhagen, 2100, Denmark
| | - Anne-Vibeke Lænkholm
- Department of Pathology, Zealand University Hospital, Sygehusvej 9, Roskilde, 4000, Denmark
| | - Søren T Skou
- Department of Physiotherapy and Occupational Therapy, The Research Unit PROgrez, Naestved- Slagelse-Ringsted Hospitals, Faelledvej 2C, 1, Slagelse, 4200, Denmark
- Department of Sports Science and Clinical Biomechanics, Research Unit for Musculoskeletal Function and Physiotherapy, University of Southern Denmark, Campusvej 55, Odense, 5230, Denmark
| | - Sandy Jack
- Clinical Experimental Sciences, Faculty of Medicine, University of Southampton, University Road, Southampton, SO17 1BJ, UK
- NIHR Southampton Biomedical Research Centre, Southampton General Hospital, MP218, Tremona Road, Southampton, SO16 6YD, UK
| | - Julie Gehl
- Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Rådmannsengen 5, Naestved, 4700, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, Copenhagen, 2200, Denmark
| | - Susanne Oksbjerg Dalton
- Department of Clinical Oncology and Palliative Care, Zealand University Hospital, Rådmannsengen 5, Naestved, 4700, Denmark
- Survivorship and Inequality in Cancer, Danish Cancer Institute, Strandboulevarden 49, Copenhagen, 2100, Denmark
- Danish Research Centre for Equality in Cancer (COMPAS), Rådmannsengen 5, Naestved, 4700, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, Copenhagen, 2200, Denmark
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Liu Y, Wang Y, Wang Y, Xie Y, Cui Y, Feng S, Yao M, Qiu B, Shen W, Chen D, Du G, Chen X, Liu Z, Li Z, Yang X, Liang C, Wu L. Early prediction of treatment response to neoadjuvant chemotherapy based on longitudinal ultrasound images of HER2-positive breast cancer patients by Siamese multi-task network: A multicentre, retrospective cohort study. EClinicalMedicine 2022; 52:101562. [PMID: 35928032 PMCID: PMC9343415 DOI: 10.1016/j.eclinm.2022.101562] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND Early prediction of treatment response to neoadjuvant chemotherapy (NACT) in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer can facilitate timely adjustment of treatment regimens. We aimed to develop and validate a Siamese multi-task network (SMTN) for predicting pathological complete response (pCR) based on longitudinal ultrasound images at the early stage of NACT. METHODS In this multicentre, retrospective cohort study, a total of 393 patients with biopsy-proven HER2-positive breast cancer were retrospectively enrolled from three hospitals in china between December 16, 2013 and March 05, 2021, and allocated into a training cohort and two external validation cohorts. Patients receiving full cycles of NACT and with surgical pathological results available were eligible for inclusion. The key exclusion criteria were missing ultrasound images and/or clinicopathological characteristics. The proposed SMTN consists of two subnetworks that could be joined at multiple layers, which allowed for the integration of multi-scale features and extraction of dynamic information from longitudinal ultrasound images before and after the first /second cycles of NACT. We constructed the clinical model as a baseline using multivariable logistic regression analysis. Then the performance of SMTN was evaluated and compared with the clinical model. FINDINGS The training cohort, comprising 215 patients, were selected from Yunnan Cancer Hospital. The two independent external validation cohorts, comprising 95 and 83 patients, were selected from Guangdong Provincial People's Hospital, and Shanxi Cancer Hospital, respectively. The SMTN yielded an area under the receiver operating characteristic curve (AUC) values of 0.986 (95% CI: 0.977-0.995), 0.902 (95%CI: 0.856-0.948), and 0.957 (95%CI: 0.924-0.990) in the training cohort and two external validation cohorts, respectively, which were significantly higher than that those of the clinical model (AUC: 0.524-0.588, P all < 0.05). The AUCs values of the SMTN within the anti-HER2 therapy subgroups were 0.833-0.972 in the two external validation cohorts. Moreover, 272 of 279 (97.5%) non-pCR patients (159 of 160 (99.4%), 53 of 54 (98.1%), and 60 of 65 (92.3%) in the training and two external validation cohorts, respectively) were successfully identified by the SMTN, suggesting that they could benefit from regime adjustment at the early-stage of NACT. INTERPRETATION The SMTN was able to predict pCR in the early-stage of NACT for HER2-positive breast cancer patients, which could guide clinicians in adjusting treatment regimes. FUNDING Key-Area Research and Development Program of Guangdong Province (No.2021B0101420006); National Natural Science Foundation of China (No.82071892, 82171920); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No.2022B1212010011); the National Science Foundation for Young Scientists of China (No.82102019, 82001986); Project Funded by China Postdoctoral Science Foundation (No.2020M682643); the Outstanding Youth Science Foundation of Yunnan Basic Research Project (202101AW070001); Scientific research fund project of Department of Education of Yunnan Province(2022J0249). Science and technology Projects in Guangzhou (202201020001;202201010513); High-level Hospital Construction Project (DFJH201805, DFJHBF202105).
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Affiliation(s)
- Yu Liu
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Ying Wang
- Department of Medical Ultrasonics, the First Affiliated Hospital of Guangzhou medical University, 151 Yanjiang West Road, 510120, China
| | - Yuxiang Wang
- Department of Ultrasound, Shanxi Cancer Hospital, Shanxi Medical University, Taiyuan, 030013, China
| | - Yu Xie
- Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, 650118, China
| | - Yanfen Cui
- Department of Radiology, Shanxi Cancer Hospital, Shanxi Medical University, Taiyuan, 030013, China
| | - Senwen Feng
- Department of General Surgery, Shenzhen YanTian district people's hospital (group), Shenzhen, 518081, China
| | - Mengxia Yao
- Department of Ultrasound, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
| | - Bingjiang Qiu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Wenqian Shen
- Department of Ultrasound, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
| | - Dong Chen
- Department of Medical Ultrasound, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming 650118, China
| | - Guoqing Du
- Department of Ultrasound, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
| | - Xin Chen
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Guangzhou, 510180, China
| | - Zaiyi Liu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
| | - Zhenhui Li
- Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, 650118, China
- Corresponding author at: Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, 650118, China.
| | - Xiaotang Yang
- Department of Radiology, Shanxi Cancer Hospital, Shanxi Medical University, Taiyuan, 030013, China
- Corresponding author at: Department of Radiology, Shanxi Cancer Hospital, Shanxi Medical University, Taiyuan, 030013, China.
| | - Changhong Liang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Corresponding author at: Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China.
| | - Lei Wu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China
- Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Corresponding author at: Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhangshan Er Road, Guangzhou 510080, China.
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Evolving Role of Risk Tailored Therapy in Early Stage HER2-Positive Breast Cancer: A Canadian Perspective. Curr Oncol 2022; 29:4125-4137. [PMID: 35735438 PMCID: PMC9221562 DOI: 10.3390/curroncol29060329] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 05/28/2022] [Accepted: 05/31/2022] [Indexed: 11/30/2022] Open
Abstract
The advent of HER2-targeted therapies has led to an important shift in the management of HER2-positive early breast cancer. However, initial treatment approaches apply uniform treatment regimens to all patients, with significant treatment-related and financial toxicities for both the patient and the health care system. Recent data demonstrates that for many patients, the chemotherapy backbone, duration and nature (mono- versus dual-targeted therapy) of the HER2 blockade can be better targeted to an individual patient’s risk of recurrence. We will provide a review of current data supporting risk tailored therapy in early stage HER2-positive breast cancer along with key completed and ongoing Canadian and international risk tailored trials. Neoadjuvant systemic therapy should now be considered for patients with clinical stage 2 disease, with greater use of non-anthracycline based chemotherapy regimens. Patients with residual disease following neoadjuvant therapy should be considered for escalated treatment with adjuvant T-DM1. Patients with stage I disease can often be managed with upfront surgery and evidence-based de-escalated adjuvant chemotherapy regimens. The modest benefit of 12- versus 6 months of adjuvant HER2 therapy and/or dual adjuvant HER2 therapy should be carefully weighed against the toxicities. All patients with HER2-positive breast cancer should be enrolled in ongoing risk tailored treatment trials whenever possible. Increasing data supports risk tailored therapy in early stage HER2-positive breast cancer in place of the routine application of aggressive and toxic systemic therapy regimens to all patients. While much progress has been made towards treatment de-escalation in appropriate patients, more is needed, as we highlight in this review. Indeed, Canadian-led clinical trials are helping to lead these efforts.
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Xia B, Wang H, Wang Z, Qian Z, Xiao Q, Liu Y, Shao Z, Zhou S, Chai W, You C, Gu Y. A Combined Nomogram Model to Predict Disease-free Survival in Triple-Negative Breast Cancer Patients With Neoadjuvant Chemotherapy. Front Genet 2021; 12:783513. [PMID: 34868273 PMCID: PMC8632946 DOI: 10.3389/fgene.2021.783513] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 10/22/2021] [Indexed: 11/13/2022] Open
Abstract
Background: To investigate whether the radiomics signature (Rad-score) of DCE-MRI images obtained in triple-negative breast cancer (TNBC) patients before neoadjuvant chemotherapy (NAC) is associated with disease-free survival (DFS). Develop and validate an intuitive nomogram based on radiomics signatures, MRI findings, and clinicopathological variables to predict DFS. Methods: Patients (n = 150) from two hospitals who received NAC from August 2011 to May 2017 were diagnosed with TNBC by pathological biopsy, and follow-up through May 2020 was retrospectively analysed. Patients from one hospital (n = 109) were used as the training group, and patients from the other hospital (n = 41) were used as the validation group. ROIs were drawn on 1.5 T MRI T1W enhancement images of the whole volume of the tumour obtained with a 3D slicer. Radiomics signatures predicting DFS were identified, optimal cut-off value for Rad-score was determined, and the associations between DFS and radiomics signatures, MRI findings, and clinicopathological variables were analysed. A nomogram was developed and validated for individualized DFS estimation. Results: The median follow-up time was 53.5 months, and 45 of 150 (30.0%) patients experienced recurrence and metastasis. The optimum cut-off value of the Rad-score was 0.2528, which stratified patients into high- and low-risk groups for DFS in the training group (p<0.001) and was validated in the external validation group. Multivariate analysis identified three independent indicators: multifocal/centric disease status, pCR status, and Rad-score. A nomogram based on these factors showed discriminatory ability, the C-index of the model was 0.834 (95% CI, 0.761-0.907) and 0.868 (95% CI, 0.787-949) in the training and the validation groups, respectively, which is better than clinicoradiological nomogram(training group: C-index = 0.726, 95% CI = 0.709-0.743; validation group: C-index = 0.774,95% CI = 0.743-0.805). Conclusion: The Rad-score derived from preoperative MRI features is an independent biomarker for DFS prediction in patients with TNBC to NAC, and the combined radiomics nomogram improved individualized DFS estimation.
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Affiliation(s)
- Bingqing Xia
- International Peace Maternity and Child Health Hospital, Shanghai, China.,Shanghai Cancer Center, Fudan University, Shanghai, China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Zhe Wang
- Shanghai United Imaging Medical Technology Co., Ltd., Shanghai, China
| | - Zhaoxia Qian
- International Peace Maternity and Child Health Hospital, Shanghai, China
| | - Qin Xiao
- Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yin Liu
- Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Zhimin Shao
- Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Shuling Zhou
- Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Weimin Chai
- Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Chao You
- Shanghai Cancer Center, Fudan University, Shanghai, China
| | - Yajia Gu
- Shanghai Cancer Center, Fudan University, Shanghai, China
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Skarping I, Förnvik D, Heide-Jørgensen U, Rydén L, Zackrisson S, Borgquist S. Neoadjuvant breast cancer treatment response; tumor size evaluation through different conventional imaging modalities in the NeoDense study. Acta Oncol 2020; 59:1528-1537. [PMID: 33063567 DOI: 10.1080/0284186x.2020.1830167] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Neoadjuvant chemotherapy (NACT) is offered to an increasing number of breast cancer (BC) patients, and comprehensive monitoring of treatment response is of utmost importance. Several imaging modalities are available to follow tumor response, although likely to provide different clinical information. We aimed to examine the association between early radiological response by three conventional imaging modalities and pathological complete response (pCR). Further, we investigated the agreement between these modalities pre-, during, and post-NACT, and the accuracy of predicting pathological residual tumor burden by these imaging modalities post-NACT. MATERIAL AND METHODS This prospective Swedish cohort study included 202 BC patients assigned to NACT (2014-2019). Breast imaging with clinically used modalities: mammography, ultrasound, and tomosynthesis was performed pre-, during, and post-NACT. We investigated the agreement of tumor size by the different imaging modalities, and their accuracy of tumor size estimation. Patients with a radiological complete response or radiological partial response (≥30% decrease in tumor diameter) during NACT were classified as radiological early responders. RESULTS Patients with an early radiological response by ultrasound had 2.9 times higher chance of pCR than early radiological non-responders; the corresponding relative chance for mammography and tomosynthesis tumor size measures was 1.8 and 2.8, respectively. Post-NACT, each modality, separately, could accurately estimate tumor size (within 5 mm margin compared to pathological evaluation) in 43-46% of all tumors. The diagnostic precision in predicting pCR post-NACT was similar between the three imaging modalities; however, tomosynthesis had slightly higher specificity and positive predictive values. CONCLUSION Breast imaging modalities correctly estimated pathological tumor size in less than half of the tumors. Based on this finding, predicting residual tumor size post-NACT is challenging using conventional imaging. Patients with early radiological non-response might need improved monitoring during NACT and be considered for changed treatment plans.
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Affiliation(s)
- Ida Skarping
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Skåne University Hospital, Lund, Sweden
| | - Daniel Förnvik
- Department of Translational Medicine, Medical Radiation Physics, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Uffe Heide-Jørgensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Lisa Rydén
- Department of Surgery, Lund University, Skåne University Hospital, Lund, Sweden
| | - Sophia Zackrisson
- Department of Translational Medicine, Diagnostic Radiology, Lund University, Skåne University Hospital, Lund, Sweden
- Department of Translational Medicine, Diagnostic Radiology, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Signe Borgquist
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Skåne University Hospital, Lund, Sweden
- Department of Oncology, Aarhus University Hospital, Aarhus, Denmark
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Yu N, Leung VWY, Meterissian S. MRI Performance in Detecting pCR After Neoadjuvant Chemotherapy by Molecular Subtype of Breast Cancer. World J Surg 2019; 43:2254-2261. [PMID: 31101952 DOI: 10.1007/s00268-019-05032-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND MRI performance in detecting pathologic complete response (pCR) post-neoadjuvant chemotherapy (NAC) in breast cancer has been previously explored. However, since tumor response varies by molecular subtype, it is plausible that imaging performance also varies. Therefore, we performed a literature review on subtype-specific MRI performance in detecting pCR post-NAC. METHODS Two reviewers searched Cochrane, PubMed, and EMBASE for articles published between 2013 and 2018 that examined MRI performance in detecting pCR post-NAC. After filtering, ten primary research articles were included. Statistical metrics, such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were extracted per study for triple negative, HR+/HER2-, and HER2+ patients. RESULTS Ten studies involving 2310 patients were included. In triple negative breast cancer, MRI showed NPV (58-100%) and PPV (72.7-94.7%) across 446 patients and sensitivity (45.5-100%) and specificity (49-94.4%) in 375 patients. In HR+/HER2- breast cancer patients, MRI showed NPV (29.4-100%) and PPV (21.4-95.1%) across 851 patients and sensitivity (43-100%) and specificity (45-93%) across 780 patients. In HER2+-enriched subtype, MRI showed NPV (62-94.6%) and PPV (34.9-72%) in 243 patients and sensitivity (36.2-83%) and specificity (47-90%) in 255 patients. CONCLUSION MRI accuracy in detecting pCR post-NAC by subtype is not as consistent, nor as high, as individual studies suggest. Larger studies using standardized pCR definition with appropriate timing of surgery and MRI need to be conducted. This study has shown that MRI is in fact not an accurate prediction of pCR, and thus, clinicians may need to rely on other approaches such as biopsies of the tumor bed.
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Affiliation(s)
- Nancy Yu
- Faculty of Medicine, McGill University, Montréal, QC, H4A3T2, Canada
| | - Vivian W Y Leung
- Faculty of Medicine, McGill University, Montréal, QC, H4A3T2, Canada
| | - Sarkis Meterissian
- Faculty of Medicine, McGill University, Montréal, QC, H4A3T2, Canada.
- Department of Oncology, McGill University, Montréal, QC, H4A3T2, Canada.
- Department of Surgery, McGill University, Montréal, QC, H3G1A4, Canada.
- Research Institute of MUHC, Glen Site, 1001 Decarie Boulevard, Montreal, QC, H4A 3J1, Canada.
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Early assessment with magnetic resonance imaging for prediction of pathologic response to neoadjuvant chemotherapy in triple-negative breast cancer: Results from the phase III BrighTNess trial. Eur J Surg Oncol 2019; 46:223-228. [PMID: 31606288 DOI: 10.1016/j.ejso.2019.10.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 09/19/2019] [Accepted: 10/02/2019] [Indexed: 01/17/2023] Open
Abstract
INTRODUCTION The ability of breast magnetic resonance imaging (MRI) to predict pathologic complete response (pCR) to neoadjuvant systemic therapy (NST) varies across biological subtypes. We sought to determine how well breast MRI findings following initial treatment on the phase III BrighTNess trial correlated with pCR in patients with triple negative breast cancer (TNBC). METHODS Baseline and mid-treatment imaging and pathologic response data were available in 519 patients with stage II-III TNBC who underwent NST as per protocol. MRI complete response (mCR) was defined as disappearance of all target lesion(s) and MRI partial response (mPR) as a ≥50% reduction in the largest tumor diameter. RESULTS Overall, mCR was demonstrated in 116 patients (22%), whereas 166 (32%) had mPR and 237 (46%) had stable/progressive disease (SD/PD). The positive predictive value (PPV), negative predictive value, and overall accuracy of the mid-treatment MRI for pCR were 78%, 56%, and 61%, respectively; accuracy did not differ significantly between gBRCA mutation carriers and non-carriers (52% vs. 63%, p = 0.10). When compared to patients with SD/PD, those with mPR or mCR were 3.35-fold (95% CI 2.07-5.41) more likely to have pCR at surgery. MRI response during NST was significantly associated with eligibility for breast-conserving surgery following completion of treatment (93.1% for mCR vs. 81.6% for SD/PD, p < 0.001). CONCLUSIONS Complete response on mid-treatment MRI in the BrighTNess trial had a PPV of 78% for demonstration of pCR after completion of NST in TNBC. However, a substantial proportion of patients with mPR or SD/PD also achieved a pCR. CLINICAL TRIAL REGISTRATION NCT02032277.
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Comparison of 99mTc-Sestamibi Molecular Breast Imaging and Breast MRI in Patients With Invasive Breast Cancer Receiving Neoadjuvant Chemotherapy. AJR Am J Roentgenol 2019; 213:932-943. [PMID: 31166752 DOI: 10.2214/ajr.18.20628] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE. The purpose of this study is to prospectively compare the size of invasive breast cancer before and after neoadjuvant chemotherapy (NAC) at breast MRI and molecular breast imaging (MBI) and to assess the accuracy of post-NAC MBI and MRI relative to pathologic analysis. SUBJECTS AND METHODS. Women with invasive breast cancer greater than or equal to 1.5 cm were enrolled to compare the longest dimension before and after NAC at MRI and MBI. MBI was performed on a dual-detector cadmium zinc telluride system after administration of 6.5 mCi (240 MBq) 99mTc-sestamibi. The accuracy of MRI and MBI in assessing residual disease (invasive disease or ductal carcinoma in situ) was determined relative to pathologic examination. RESULTS. The longest dimension at MRI was within 1.0 cm of that at MBI in 72.3% of cases before NAC and 70.1% of cases after NAC. The difference between the longest dimension at imaging after NAC and pathologic tumor size was within 1 cm for 58.7% of breast MRI cases and 59.6% of MBI cases. Ninety patients underwent both MRI and MBI after NAC. In the 56 patients with invasive residual disease, 10 (17.9%) cases were negative at MRI and 23 (41.1%) cases were negative at MBI. In the 34 patients with breast pathologic complete response, there was enhancement in 10 cases (29.4%) at MRI and uptake in six cases (17.6%) at MBI. Sensitivity, specificity, positive predictive value, and negative predictive value after NAC were 82.8%, 69.4%, 81.4%, and 71.4%, respectively, for MRI and 58.9%, 82.4%, 84.6%, and 54.9%, respectively, for MBI. CONCLUSION. Breast MRI and MBI showed similar disease extent before NAC. MBI may be an alternative to breast MRI in patients with a contraindication to breast MRI. Neither modality showed sufficient accuracy after NAC in predicting breast pathologic complete response to obviate tissue diagnosis to assess for residual invasive disease. Defining the extent of residual disease compared with pathologic evaluation was also limited after NAC for both breast MRI and MBI.
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Mazari FAK, Sharma N, Dodwell D, Horgan K. Human Epidermal Growth Factor 2-positive Breast Cancer with Mammographic Microcalcification: Relationship to Pathologic Complete Response after Neoadjuvant Chemotherapy. Radiology 2018; 288:366-374. [PMID: 29786482 DOI: 10.1148/radiol.2018170960] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2024]
Abstract
Purpose To determine the relationship between the presence or absence of mammographic calcifications in human epidermal growth factor receptor 2 (HER2)-positive breast cancers and pathologic complete response (pCR) to neoadjuvant chemotherapy and to determine other tumor and clinical characteristics that may be predictive of such a response. Materials and Methods A database of all patients with HER2-positive breast cancer who underwent neoadjuvant chemotherapy between 2007 and 2015 was retrospectively reviewed. Patient demographic characteristics, mammographic appearance, molecular subtype of cancer (luminal or nonluminal), radiologic response (based on breast magnetic resonance images), surgery, and pathologic response to treatment were recorded. Inter- and subgroup comparison was performed for presence of mammographic microcalcification and cancer subtype by using Mann-Whitney and χ2 tests and logistic regression. Results A total of 111 patients with a median age of 49 years (interquartile range, 40-57 years) were evaluated. Of these, 64.9% (72 of 111) had mammographic microcalcifications, 63.1% (70 of 111) had luminal B cancer, and 36.9% (41 of 111) had nonluminal HER2-positive cancer. Radiologic response to neoadjuvant chemotherapy was observed in 70.3% (78 of 111) of patients. Surgery was performed in 97.3% (108 of 111) of patients, and 30.6% (34 of 111) of patients underwent breast conservation. pCR was observed in 33.3% (37 of 111) of patients; 16.2% (18 of 111) showed residual ductal carcinoma in situ and 50.5% (56 of 111) had residual invasive disease. The pCR rate was the same (P = .21) in patients with mammographic microcalcification (29.2% [21 of 72]) as in those without calcification (41.0% [16 of 39]). The pCR rate in patients with nonluminal HER2-positive cancers (46.3% [19 of 41]) was higher (P = .01) than in those with luminal B cancers (25.7% [18 of 70]). pCR was associated with nonluminal HER2-positive subtype (odds ratio, 5.4; 95% confidence interval: 1.8, 16.0; P = .01) and complete radiologic response (odds ratio, 20.4; 95% confidence interval: 3.3, 126.6; P = .01). Conclusion Patients with HER2-positive cancer and mammographic microcalcification can achieve pCR after neoadjuvant chemotherapy. Nonluminal HER2-positive subtype and complete radiologic response are predictors of pCR.
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Affiliation(s)
- Fayyaz A K Mazari
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
| | - Nisha Sharma
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
| | - David Dodwell
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
| | - Kieran Horgan
- From the Leeds Breast Unit (F.A.K.M., K.H.) and the Departments of Radiology (N.S.) and Oncology (D.D.), Leeds Teaching Hospitals NHS Trust, St James's University Hospital, Beckett Street, Leeds LS9 7TF, England
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Abstract
Neoadjuvant chemotherapy (NAC) has become an important treatment approach for stage II/III breast cancers to downsize tumor and enable breast-conserving surgery for patients that may otherwise undergo mastectomy. MR imaging has the potential to identify early response or disease progression, enabling potential modification to NAC regimens. Detection of size and morphologic changes is better appreciated with MR imaging than other modalities and is different between molecular subtypes of breast cancer. The combination of DCE-MR imaging and DWI provides the highest sensitivity and specificity. Other new modalities such as FDG PET/MR imaging and molecular breast imaging are still undergoing research.
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Affiliation(s)
- Huong T Le-Petross
- Department of Diagnostic Imaging, University of Texas MD Anderson Cancer Center, 1155 Pressler Street, Houston, TX 77030, USA.
| | - Bora Lim
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, 1155 Pressler Street, Houston, TX 77030, USA
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Rauch GM, Adrada BE, Kuerer HM, van la Parra RFD, Leung JWT, Yang WT. Multimodality Imaging for Evaluating Response to Neoadjuvant Chemotherapy in Breast Cancer. AJR Am J Roentgenol 2017; 208:290-299. [DOI: 10.2214/ajr.16.17223] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/30/2023]
Affiliation(s)
- Gaiane M. Rauch
- Department of Diagnostic Radiology, Unit 1473, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030-4009
| | - Beatriz Elena Adrada
- Department of Diagnostic Radiology, Unit 1350, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Henry Mark Kuerer
- Department of Breast Surgical Oncology, Unit 1434, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Raquel F. D. van la Parra
- Department of Breast Surgical Oncology, Unit 1434, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Jessica W. T. Leung
- Department of Diagnostic Radiology, Unit 1350, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wei Tse Yang
- Department of Diagnostic Radiology, Unit 1459, The University of Texas MD Anderson Cancer Center, Houston, TX
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